code: def __init__(
      self,
      in_channels=[116, 232, 464],
      out_channels=96,
      act="leaky_relu",
  ):
      super(Channel_T, self).__init__()
      self.convs = nn.LayerList()
      for i in range(len(in_channels)):
          self.convs.append(
              ConvBNLayer(in_channels[i], out_channels, 1, act=act)
          )
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle import ParamAttr
label_desc: Use image node_id 1 to create a new Channel_T object from inherited base classes: nn with example: obj = Channel_T(in_channels, out_channels, act)